Insurance, Biases, Discrimination and Fairness
This book offers an introduction to the technical foundations of discrimination and equity issues in insurance models, catering to undergraduates, postgraduates, and practitioners. It is a self-contained resource, accessible to those with a basic understanding of probability and statistics. Designed...
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| 第一著者: | |
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| 団体著者: | |
| フォーマット: | 電子媒体 eBook |
| 言語: | 英語 |
| 出版事項: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| 版: | 1st ed. 2024. |
| シリーズ: | Springer Actuarial,
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| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1007/978-3-031-49783-4 |
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目次:
- Introduction
- Part I Insurance and Predictive Modeling
- Fundamentals of Actuarial Pricing
- Models: Overview on Predictive Models
- Models: Interpretability, Accuracy and Calibration
- Part II Data
- What Data?
- Some Examples of Discrimination
- Observations or Experiments: Data in Insurance
- Part III Fairness
- Group Fairness
- Individual Fairness
- Part IV Mitigation
- Pre-processing
- In-processing
- Post-processing.